High-dose methotrexate and rituximab induction regimen in immunocompetent patients with primary CNS lymphoma: a retrospective single-center study of survival predictors.

PURPOSE: Primary Central Nervous System Lymphoma (PCNSL) is an aggressive tumor that is confined to the CNS. Although the provision of high-dose methotrexate (HD-MTX) has remarkably improved outcomes in PCNSL patients, the optimal treatment regimens and standard MTX dose for induction therapy have been largely controversial. Herein, we sought to explore the impact of adjuvant rituximab and different dosages of induction HD-MTX on survival outcomes of immunocompetent patients with PCNSL. METHODS: In this study, we examined patients with PCNSL treated at a single NCI-designated comprehensive cancer center to evaluate their survival outcomes. We conducted a retrospective analysis of 51 immunocompetent patients with PCNSL who received their induction chemotherapy at the University of Alabama at Birmingham (UAB) between 2001 and 2019. Only adult patients with a confirmed diagnosis of PCNSL who had either HD-MTX alone or in combination with rituximab were included. Patients' demographics, clinical characteristics, and survival data were collected and analyzed. RESULTS: There is no significant difference in survival among patients who received MTX alone versus MTX plus rituximab (HR = 0.996 (95% CI: 0.398-2.493), p = 0.994). Lower doses of MTX were associated with worse survival outcomes (HR = 0.680 (95% CI: 0.530-0.872), p = 0.002); however, this difference in survival was not significant when adjusted to age (HR = 0.797 (95% CI: 0.584-1.088), p = 0.153). CONCLUSION: Our experience challenges the role of rituximab in PCNSL during induction therapy. Our study also highlights the shorter survival in elderly patients with PCNSL which can be related, to some extent, to the relatively lower doses of HD-MTX. There is an unmet need to establish a consensus on the most effective upfront regimen in PCNSL through prospective studies.

Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge.

PURPOSE: The aim of the 2016 quantitative susceptibility mapping (QSM) reconstruction challenge was to test the ability of various QSM algorithms to recover the underlying susceptibility from phase data faithfully. METHODS: Gradient-echo images of a healthy volunteer acquired at 3T in a single orientation with 1.06 mm isotropic resolution. A reference susceptibility map was provided, which was computed using the susceptibility tensor imaging algorithm on data acquired at 12 head orientations. Susceptibility maps calculated from the single orientation data were compared against the reference susceptibility map. Deviations were quantified using the following metrics: root mean squared error (RMSE), structure similarity index (SSIM), high-frequency error norm (HFEN), and the error in selected white and gray matter regions. RESULTS: Twenty-seven submissions were evaluated. Most of the best scoring approaches estimated the spatial frequency content in the ill-conditioned domain of the dipole kernel using compressed sensing strategies. The top 10 maps in each category had similar error metrics but substantially different visual appearance. CONCLUSION: Because QSM algorithms were optimized to minimize error metrics, the resulting susceptibility maps suffered from over-smoothing and conspicuity loss in fine features such as vessels. As such, the challenge highlighted the need for better numerical image quality criteria. Magn Reson Med 79:1661-1673, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Comparison of image sensitivity between conventional tensor-based and fast diffusion kurtosis imaging protocols in a rodent model of acute ischemic stroke.

Diffusion kurtosis imaging (DKI) can offer a useful complementary tool to routine diffusion MRI for improved stratification of heterogeneous tissue damage in acute ischemic stroke. However, its relatively long imaging time has hampered its clinical application in the emergency setting. A recently proposed fast DKI approach substantially shortens the imaging time, which may help to overcome the scan time limitation. However, to date, the sensitivity of the fast DKI protocol for the imaging of acute stroke has not been fully described. In this study, we performed routine and fast DKI scans in a rodent model of acute stroke, and compared the sensitivity of diffusivity and kurtosis indices (i.e. axial, radial and mean) in depicting acute ischemic lesions. In addition, we analyzed the contrast-to-noise ratio (CNR) between the ipsilateral ischemic and contralateral normal regions using both conventional and fast DKI methods. We found that the mean kurtosis shows a relative change of 47.1 ± 7.3% between the ischemic and contralateral normal regions, being the most sensitive parameter in revealing acute ischemic injury. The two DKI methods yielded highly correlated diffusivity and kurtosis measures and lesion volumes (R(2) ⩾ 0.90, p < 0.01). Importantly, the fast DKI method exhibited significantly higher CNR of mean kurtosis (1.6 ± 0.2) compared with the routine tensor protocol (1.3 ± 0.2, p < 0.05), with its CNR per unit time (CNR efficiency) approximately doubled when the scan time was taken into account. In conclusion, the fast DKI method provides excellent sensitivity and efficiency to image acute ischemic tissue damage, which is essential for image-guided and individualized stroke treatment.

Neuropsychological performance, brain imaging, and driving violations in multiple sclerosis.

OBJECTIVE: To examine the relationship between third ventricular width, a measure of thalamic brain atrophy, and motor vehicle violation type and frequency in a cohort of patients with multiple sclerosis (MS). DESIGN: Retrospective cohort study. SETTING: Tertiary care university hospital. PARTICIPANTS: Thirty-five individuals with clinically confirmed relapsing-remitting multiple sclerosis and 35 age-, sex-, and education-matched community-dwelling healthy comparisons (N=70). Participants were aged between 25 and 65 years. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Data on motor vehicle violations were obtained from an online database (Iowa Courts Online). The violations were categorized as follows: (1) speeding, (2) nonmoving safety, (3) administrative, (4) alcohol-related offense, (5) moving safety, and (6) total violations. Neuropsychological performance in all major cognitive domains was obtained. Thalamic atrophy for the patients with MS was determined via third ventricular width measurement. RESULTS: The MS group had a greater number of overall violations, administrative violations, and nonmoving safety violations. The groups differed on neuropsychological tasks measuring visuospatial skills, speeded language, learning, and executive functioning, after controlling for affective symptoms. Third ventricular width was associated with total violations as well as moving safety violations. Finally, third ventricular width accounted for a significant variance in driving violation frequency above and beyond demographic variables and neuropsychological factors. CONCLUSIONS: There is an increased frequency of motor vehicle violations among patients with multiple sclerosis, and the number of violations can be predicted by thalamic brain atrophy.

Robust AI-Driven Segmentation of Glioblastoma T1c and FLAIR MRI Series and the Low Variability of the MRIMath© Smart Manual Contouring Platform.

Patients diagnosed with glioblastoma multiforme (GBM) continue to face a dire prognosis. Developing accurate and efficient contouring methods is crucial, as they can significantly advance both clinical practice and research. This study evaluates the AI models developed by MRIMath© for GBM T1c and fluid attenuation inversion recovery (FLAIR) images by comparing their contours to those of three neuro-radiologists using a smart manual contouring platform. The mean overall Sørensen-Dice Similarity Coefficient metric score (DSC) for the post-contrast T1 (T1c) AI was 95%, with a 95% confidence interval (CI) of 93% to 96%, closely aligning with the radiologists' scores. For true positive T1c images, AI segmentation achieved a mean DSC of 81% compared to radiologists' ranging from 80% to 86%. Sensitivity and specificity for T1c AI were 91.6% and 97.5%, respectively. The FLAIR AI exhibited a mean DSC of 90% with a 95% CI interval of 87% to 92%, comparable to the radiologists' scores. It also achieved a mean DSC of 78% for true positive FLAIR slices versus radiologists' scores of 75% to 83% and recorded a median sensitivity and specificity of 92.1% and 96.1%, respectively. The T1C and FLAIR AI models produced mean Hausdorff distances (<5 mm), volume measurements, kappa scores, and Bland-Altman differences that align closely with those measured by radiologists. Moreover, the inter-user variability between radiologists using the smart manual contouring platform was under 5% for T1c and under 10% for FLAIR images. These results underscore the MRIMath© platform's low inter-user variability and the high accuracy of its T1c and FLAIR AI models.

CEST2022 - mapping multi-pool CEST signal changes in an animal model of brain tumor with quasi-steady-state reconstruction-empowered CEST quantification.

Chemical exchange saturated transfer (CEST) MRI has biomarker potential to assess tissue microenvironment in brain tumors. Multi-pool Lorentzian or spinlock models provides useful insights into the CEST contrast mechanism. However, T1 contribution to the complex overlapping effects of brain tumors is difficult under the non-equilibrium state. Therefore, this study evaluated T1 contributions on multi-pool parameters with quasi-steady-state (QUASS) algorithm reconstructed equilibrium data. MRI scans were performed in rat brain tumor models, including relaxation, diffusion, and CEST imaging. A pixel-wise seven-pool spinlock-model was employed to fit QUASS reconstructed CEST Z-spectra and evaluated the magnetization transfer (MT), amide, amine, guanidyl, and nuclear-overhauled effect (NOE) signals in tumor and normal tissues. In addition, T1 was estimated from the spinlock-model fitting and compared with measured T1. We observed tumor had a statistically significant increase in the amide signal (p < 0.001) and decreases in the MT and NOE signals (p < 0.001). On the other hand, the differences in amine and guanidyl between the tumor and contralateral normal regions were not statistically significant. The differences between measured and estimated T1 values were 8% in the normal tissue and 4% in the tumor. Furthermore, the isolated MT signal strongly correlated with R1 (r = 0.96, P < 0.001). In summary, we successfully unraveled multi-factorial effects in the CEST signal using spinlock-model fitting and QUASS method and demonstrated the effect of T1 relaxation on MT and NOE.

Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas.

PURPOSE: The Response Assessment in Neuro-Oncology (RANO) criteria for lower-grade gliomas (LGGs) define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator's discretion of the perpendicular diameter of the largest tumor cross-section. Potential sources of error include acquisition inconsistency of 2D slices, operator selection variabilities in both representative tumor cross-section and measurement line locations, and the inability to quantify infiltrative tumor margins and satellite lesions. Our goal was to assess the accuracy and reproducibility of RANO in LG. MATERIALS AND METHODS: A total of 651 FLAIR MRIs from 63 participants with LGGs were retrospectively analyzed by three blinded attending physicians and three blinded resident trainees using RANO criteria, 2D visual assessment, and computer-assisted 3D volumetric assessment. RESULTS: RANO product measurements had poor-to-moderate inter-operator reproducibility (r2 = 0.28-0.82; coefficient of variance (CV) = 44-110%; mean percent difference (diff) = 0.4-46.8%) and moderate-to-excellent intra-operator reproducibility (r2 = 0.71-0.88; CV = 31-58%; diff = 0.3-23.9%). When compared to 2D visual ground truth, the accuracy of RANO compared to previous and baseline scans was 66.7% and 65.1%, with an area under the ROC curve (AUC) of 0.67 and 0.66, respectively. When comparing to volumetric ground truth, the accuracy of RANO compared to previous and baseline scans was 21.0% and 56.5%, with an AUC of 0.39 and 0.55, respectively. The median time delay at diagnosis was greater for false negative cases than for false positive cases for the RANO assessment compared to previous (2.05 > 0.50 years, p = 0.003) and baseline scans (1.08 > 0.50 years, p = 0.02). CONCLUSION: RANO-based assessment of LGGs has moderate reproducibility and poor accuracy when compared to either visual or volumetric ground truths.

Fast diffusion kurtosis imaging in acute ischemic stroke shows mean kurtosis-diffusivity mismatch.

BACKGROUND AND PURPOSE: Diffusion kurtosis imaging (DKI) is an advanced technique more specific to irreversible ischemic injury than conventional diffusion-weighted imaging (DWI). However, its clinical translation has been limited by a long acquisition time and complex postprocessing. METHODS: A fast DKI sequence (3 minutes) was implemented on a 3T MRI (Siemens Trio) and piloted as part of an inpatient brain MRI protocol. Mean kurtosis (MK) and mean diffusivity (MD) maps were postprocessed automatically at the scanner console and sent to the Picture Archiving and Communications System. We retrospectively reviewed consecutive patients in a 5-month period with acute ischemic stroke due to large vessel occlusion. MK and MD of the ischemic infarcts and contralateral normal brain were measured, and lesion volumes were measured in large infarcts using semiautomated segmentation. RESULTS: Twenty-two patients were included in the study (median age 66). The median time from last known well to MRI was 37 hours. MD and MK maps were successfully processed and demonstrated acute infarction in concordance with DWI in all cases. Infarcted regions had higher MK and lower MD compared to contralateral normal-appearing regions. MK lesion volume was significantly smaller than MD volume. CONCLUSION: In this pilot study, we demonstrated the feasibility of incorporating a fast DKI sequence into a clinical MRI protocol. Acute infarcts were depicted on kurtosis maps, and MK lesion volumes were smaller than MD, in accordance with prior works. Future studies are needed to determine the role of DKI in acute stroke treatment selection and prognostication.

Undesired impact of iron supplement on MRI assessment of post-treatment glioblastoma.

Glioblastoma (GBM) is the most common malignant adult brain and has a poor prognosis. Routine post-treatment MRI evaluations are required to assess treatment response and disease progression. We present a case of an 83-year-old female who underwent MRI assessment of post-treatment GBM after intravenous iron replacement therapy, ferumoxytol. The brain MRI revealed unintended alteration of MRI signal characteristics from the iron containing agent which confounded diagnostic interpretation and subsequently, the treatment planning. Ferumoxytol injection prior to contrast enhanced MRI must be screened in post-treatment GBM patients to accurately evaluate tumor activity.

The effect of procedural end-tidal CO2 on infarct expansion during anterior circulation thrombectomy.

BACKGROUND: Carbon dioxide is a potent cerebral vasodilator that may influence outcomes after ischemic stroke. The objective of this study was to investigate the effect of intraprocedural mean end-tidal CO2 (ETCO2) levels on core infarct expansion and neurologic outcome following thrombectomy for anterior circulation ischemic stroke. METHODS: A retrospective review was conducted of consecutive patients from March 2020 to June 2021 who underwent mechanical thrombectomy for acute anterior circulation ischemic stroke under general anesthesia and achieved successful recanalization (Thrombolysis in Cerebral Infarction [TICI] ≥ 2b). Only patients with CT perfusion, procedural ETCO2, and postoperative MRI data were included. Segmentation software was used for multi-parametric image analysis. Normocarbia defined as mean ETCO2 of 35 mmHg was used to dichotomize subjects. Univariate and multivariate statistics were applied. RESULTS: Fifty-eight patients met criteria for analysis. Of these, 44 had TICI 3 recanalization, 9 had TICI 2c, and 5 had TICI 2b. Within this combined recanalization group, patients with mean ETCO2 > 35 had significantly higher rates of functional independence at 90 days. Although patients tended to salvage more penumbra and experience smaller final infarcts when ETCO2 exceeded 35 mmHg, this did not reach statistical significance. CONCLUSIONS: Stroke patients who underwent successful thrombectomy with general anesthesia achieved higher rates of functional independence when procedural ETCO2 exceeded 35 mmHg. Further studies to confirm this effect and investigate optimal ETCO2 parameters should be considered.

Evaluation of negation and uncertainty detection and its impact on precision and recall in search.

Radiology reports contain information that can be mined using a search engine for teaching, research, and quality assurance purposes. Current search engines look for exact matches to the search term, but they do not differentiate between reports in which the search term appears in a positive context (i.e., being present) from those in which the search term appears in the context of negation and uncertainty. We describe RadReportMiner, a context-aware search engine, and compare its retrieval performance with a generic search engine, Google Desktop. We created a corpus of 464 radiology reports which described at least one of five findings (appendicitis, hydronephrosis, fracture, optic neuritis, and pneumonia). Each report was classified by a radiologist as positive (finding described to be present) or negative (finding described to be absent or uncertain). The same reports were then classified by RadReportMiner and Google Desktop. RadReportMiner achieved a higher precision (81%), compared with Google Desktop (27%; p < 0.0001). RadReportMiner had a lower recall (72%) compared with Google Desktop (87%; p = 0.006). We conclude that adding negation and uncertainty identification to a word-based radiology report search engine improves the precision of search results over a search engine that does not take this information into account. Our approach may be useful to adopt into current report retrieval systems to help radiologists to more accurately search for radiology reports.

A study of diffusion tensor imaging by tissue-specific, smoothing-compensated voxel-based analysis.

Voxel-based analysis (VBA) is commonly used for statistical analysis of image data, including the detection of significant signal differences between groups. Typically, images are co-registered and then smoothed with an isotropic Gaussian kernel to compensate for image misregistration, to improve the signal-to-noise ratio (SNR), to reduce the number of multiple comparisons, and to apply random field theory. Problems with typical implementations of VBA include poor tissue specificity from image misregistration and smoothing. In this study, we developed a new tissue-specific, smoothing-compensated (T-SPOON) method for the VBA of diffusion tensor imaging (DTI) data with improved tissue specificity and compensation for image misregistration and smoothing. When compared with conventional VBA methods, the T-SPOON method introduced substantially less errors in the normalized and smoothed DTI maps. Another confound of the conventional DTI-VBA is that it is difficult to differentiate between differences in morphometry and DTI measures that describe tissue microstructure. T-SPOON VBA decreased the effects of differential morphometry in the DTI VBA studies. T-SPOON and conventional VBA were applied to a DTI study of white matter in autism. T-SPOON VBA results were found to be more consistent with region of interest (ROI) measurements in the corpus callosum and temporal lobe regions. The T-SPOON method may be also applicable to other quantitative imaging maps such as T1 or T2 relaxometry, magnetization transfer, or PET tracer maps.

fMRI evidence for multisensory recruitment associated with rapid eye movements during sleep.

We studied the neural correlates of rapid eye movement during sleep (REM) by timing REMs from video recording and using rapid event-related functional MRI. Consistent with the hypothesis that REMs share the brain systems and mechanisms with waking eye movements and are visually-targeted saccades, we found REM-locked activation in the primary visual cortex, thalamic reticular nucleus (TRN), 'visual claustrum', retrosplenial cortex (RSC, only on the right hemisphere), fusiform gyrus, anterior cingulate cortex, and the oculomotor circuit that controls awake saccadic eye movements (and subserves awake visuospatial attention). Unexpectedly, robust activation also occurred in non-visual sensory cortices, motor cortex, language areas, and the ascending reticular activating system, including basal forebrain, the major source of cholinergic input to the entire cortex. REM-associated activation of these areas, especially non-visual primary sensory cortices, TRN and claustrum, parallels findings from waking studies on the interactions between multiple sensory data, and their 'binding' into a unified percept, suggesting that these mechanisms are also shared in waking and dreaming and that the sharing goes beyond the expected visual scanning mechanisms. Surprisingly, REMs were associated with a decrease in signal in specific periventricular subregions, matching the distribution of the serotonergic supraependymal plexus. REMs might serve as a useful task-free probe into major brain systems for functional brain imaging.

Diffusion tensor imaging in schizophrenia: relationship to symptoms.

In this diffusion tensor imaging (DTI) study, the authors investigated white matter integrity in schizophrenia and the relationships between white matter alterations and specific symptoms of the disorder. We compared DTI images of 25 schizophrenia patients and 25 matched healthy controls and performed voxel-wise correlational analyses using the patient's DTI data and their severity scores of positive and negative symptoms. We found diffuse deficits in multiple types of white matter tracts in schizophrenia, and an inverse relationship of DTI fractional anisotropy (FA) values with positive symptom scores in association fibers, supporting a "disconnection" hypothesis of positive symptoms in schizophrenia.

Sporadic Hemangioblastoma of the Cavernous Sinus and Meckel's Cave.

Objectives To describe an extremely rare case of sporadic hemangioblastoma (HB) within the cavernous sinus and Meckel's cave with extension to the cerebellopontine angle (CPA) cistern. Methods A 73-year-old male presented with hearing loss, unilateral ptosis, and facial numbness. Results The imaging showed a complex cystic-solid mass centered at the left cavernous sinus and Meckel's cave with extension to the CPA cistern. Patient underwent retrosigmoid craniectomy for partial resection of the CPA angle component of the mass. Surgical pathology confirmed the diagnosis of HB and patient was scheduled for subsequent radiotherapy of the residual mass. Conclusions We present an exceptional case of supratentorial HB without associated von Hippel-Lindau (VHL) disease, which was predominantly located in the cavernous sinus and Meckel's cave and led to multiple cranial nerve symptoms. We describe imaging characteristics and radiologic-pathologic correlation of this atypically located HB, which can be difficult to consider in the differential diagnosis presurgically.

DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking.

A versatile resource program was developed for diffusion tensor image (DTI) computation and fiber tracking. The software can read data formats from a variety of MR scanners. Tensor calculation is performed by solving an over-determined linear equation system using least square fitting. Various types of map data, such as tensor elements, eigenvalues, eigenvectors, diffusion anisotropy, diffusion constants, and color-coded orientations can be calculated. The results are visualized interactively in orthogonal views and in three-dimensional mode. Three-dimensional tract reconstruction is based on the Fiber Assignment by Continuous Tracking (FACT) algorithm and a brute-force reconstruction approach. To improve the time and memory efficiency, a rapid algorithm to perform the FACT is adopted. An index matrix for the fiber data is introduced to facilitate various types of fiber bundles selection based on approaches employing multiple regions of interest (ROIs). The program is developed using C++ and OpenGL on a Windows platform.

Diffusion tensor imaging in schizophrenia.

BACKGROUND: Diffusion tensor imaging (DTI) is a relatively new neuroimaging technique that can be used to examine the microstructure of white matter in vivo. A systematic review of DTI studies in schizophrenia was undertaken to test the hypothesis that DTI can detect white matter differences between schizophrenia patients and normal control subjects. METHODS: EMBASE, PubMed, Medline, and PsychInfo were searched online and key journals were searched manually for studies comparing anisotropy (a measure of white matter integrity) between patients and control subjects. Nineteen articles were systematically reviewed. RESULTS: Though 16 studies found differences, methodological and data differences prevented a meta-analysis. Fourteen studies found reduced anisotropy in patients; two studies found only a loss of normal asymmetry. The region of investigation varied across studies, however, and when the same region (for example, the cingulum) was examined in different studies, as many failed to find a difference as found one. These inconsistencies may be the result of small sample sizes and differences in methodology. CONCLUSIONS: Diffusion tensor imaging has yet to provide consistent findings of white matter abnormalities in schizophrenia. Its potential as a means of examining anatomical connectivity may be realized with the study of larger, more homogenous groups of subjects and with ongoing improvements in image analysis.

A review of optimization and quantification techniques for chemical exchange saturation transfer MRI toward sensitive in vivo imaging.

Chemical exchange saturation transfer (CEST) MRI is a versatile imaging method that probes the chemical exchange between bulk water and exchangeable protons. CEST imaging indirectly detects dilute labile protons via bulk water signal changes following selective saturation of exchangeable protons, which offers substantial sensitivity enhancement and has sparked numerous biomedical applications. Over the past decade, CEST imaging techniques have rapidly evolved owing to contributions from multiple domains, including the development of CEST mathematical models, innovative contrast agent designs, sensitive data acquisition schemes, efficient field inhomogeneity correction algorithms, and quantitative CEST (qCEST) analysis. The CEST system that underlies the apparent CEST-weighted effect, however, is complex. The experimentally measurable CEST effect depends not only on parameters such as CEST agent concentration, pH and temperature, but also on relaxation rate, magnetic field strength and more importantly, experimental parameters including repetition time, RF irradiation amplitude and scheme, and image readout. Thorough understanding of the underlying CEST system using qCEST analysis may augment the diagnostic capability of conventional imaging. In this review, we provide a concise explanation of CEST acquisition methods and processing algorithms, including their advantages and limitations, for optimization and quantification of CEST MRI experiments.

Functional MRI study of a serial reaction time task in Huntington's disease.

The aim of this study was to investigate pathophysiological changes at an early stage of clinical Huntington's disease (HD) using a functional magnetic resonance imaging (fMRI) study and a serial reaction time task paradigm. Mildly affected and presymptomatic HD subjects (n = 8) and healthy normal controls (NC, n = 12) were studied. A group behavioral effect of implicit learning was seen only in the control population. Individual statistical parametric mapping (SPM) analysis showed more consistent activation of the caudate nucleus and putamen in the NC group. In the HD group, the group average SPM showed significant activation in the right head of caudate nucleus, as well as bilateral thalami, left middle temporal, right superior temporal, right superior frontal, right middle and inferior frontal and right postcentral gyri. In the comparison of between-group differences (NC-HD), reduced activation in the HD group relative to NC was observed in the right middle frontal, left middle occipital, left precuneus, and left middle frontal gyri. The variable striatal activity in the Huntington's group suggests early functional loss possibly associated with previously demonstrated early atrophy of these same neural structures.

Epithelioid hemangioma of the spine: Two cases.

We report two cases of epithelioid hemangioma (EH) manifested in the thoracic spine with associated clinical, radiographic, and pathological findings. Epithelioid hemangioma is a benign vascular tumor that can involve any bone (including the spine in a subset of patients). Although recognized as a benign tumor by the WHO, it can display locally aggressive features. Within the spine, these features may lead to pain, instability, and/or neurologic dysfunction. The radiographic appearance is most typically that of a lytic, well-defined lesion on plain film or CT. The MRI appearance is typically hypointense on T1WI, hyperintense on T2WI, and avidly enhancing, often with an extraosseous soft-tissue component.